Your SlideShare is downloading. ×
S-CUBE LP: A Soft-Constraint Based Approach to QoS-Aware Service Selection
Upcoming SlideShare
Loading in...5
×

Thanks for flagging this SlideShare!

Oops! An error has occurred.

×
Saving this for later? Get the SlideShare app to save on your phone or tablet. Read anywhere, anytime – even offline.
Text the download link to your phone
Standard text messaging rates apply

S-CUBE LP: A Soft-Constraint Based Approach to QoS-Aware Service Selection

992

Published on

Published in: Technology, Business
0 Comments
1 Like
Statistics
Notes
  • Be the first to comment

No Downloads
Views
Total Views
992
On Slideshare
0
From Embeds
0
Number of Embeds
2
Actions
Shares
0
Downloads
4
Comments
0
Likes
1
Embeds 0
No embeds

Report content
Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
No notes for slide

Transcript

  • 1. S-Cube Learning PackageA Soft-Constraint Based Approach to QoS-Aware Service Selection Université Paris-DESCARTES Mohamed-Anis ZEMNI, Salima BENBERNOU, Manuel CARRO www.s-cube-network.eu
  • 2. Learning Package Categorization S-Cube Quality Definition, Negotiation and Assurance Quality Management and Prediction Analysis Operations on SLAs: Detecting and Explaining Conflicting SLAs
  • 3. Service Selection and QoS Service selection is the first step to improve service composition within Service-Oriented-Architecture (SOA): •  Searches for services fitting users’ requirements •  Explores services’ properties •  Aims at putting together several elementary services •  Generates new value-added service Quality of Service (QoS) for selection often critically important: •  Software services expose not only functional characteristics, but also non-functional attributes describing their QoS •  Defines the service level (Key Performance Indicator) •  A service fulfilling all the functionality but with low QoS is not interesting
  • 4. Learning Package Overview  Problem Description  Extending SCSP with Penalties & new SLA Model  Conclusions
  • 5. Problem Description: Service Selection Scenario Select only one service among the available services that have the same functionalities but with different QoS Functionalities + QoSUser request (criteria) 1 2 Used Approach at Design-time
  • 6. Problem Description:Service Selection Techniques in the Literature 1  Constraint Satisfaction Problem (CSP): •  Classical formulation of constraints •  Quite expressive to represent several real life problems •  Defines a set of variables, each of them ranging on a finite domain, and a set of constraints restricting the values that these variables can take simultaneously •  All the constraints must be satisfied simultaneously ! Lack of built-in capabilities to express preferences among constraints and the lack of possibility of giving approximate solutions for problems which are overconstrained
  • 7. Problem Description:Service Selection Techniques in the Literature 1 Soft Constraint Satisfaction Problem (SCSP) •  Include the concept of preferences into every constraint in order to obtain a suitable solution which can be optimal or, in general, a reasonable estimation, maybe at the expense of not fulfilling all constraints •  Relies on composing the constraints in order to obtain the optimal solution •  Applied to the requirements (in terms of preferences) of the users ! Only one solution returned that is optimal * Stefano Bistarelli, Ugo Montanari, and Francesca Rossi. Semiring- based constraint satisfaction and optimization. J. ACM, 44(2):201– 236, 1997
  • 8. Problem Description: Service Selection Techniques in the Literature 1 C-semi-ring : Algebraic structure Only one domain for all variablesExample : Searching for services Available at y% of the time and with reputation = z
  • 9. Problem Description: Problem at Design-time 2.  I have to fix new criteria 1.  Required criteria cannot match any service!!!User request (criteria)
  • 10. Problem Description:Problem at Runtime ! Some problems, encountered by the service may lead to service malfunctions activity interrupted, must apply penalty!!! Out of service Out of service contract violation
  • 11. Problem Description:SLASLA - Definition: “An XML document and a contract for… •  Advertising the quality level of the services •  Taking note about the user preferences •  …” I want an SLA ensuring the performances I am searching for Propertie s Pro perties QoS ?
  • 12. Problem Description: 2Problem at Runtime Where are My preferencesand the penalties? Out of service Out of service
  • 13. Learning Package Overview  Problem Description  Extending SCSP with Penalties & new SLA Model  Conclusions
  • 14. Main ObjectiveAutomatically switch from a faultyservice to a new one User request (preferences, … Out of service Out of penalties) service Design-time Runtime
  • 15. Approach Main Points Definition of Soft Service Level Agreement (SSLA) an SLA model extended with preferences and penalties Extension of Soft Constraint Solving Problem handling penalties: Define in SSLA the penalty artifacts, such that, if a selected service failed, another one should replace it that fitting with the agreed QoS in the contract with penalties if some of them are not fulfilled SSLA to SCSP mapping
  • 16. Kinds of penalties Arithmetical Penalties •  In relation with measurable qualities of service •  Direct relation to service variables •  E.g. availability, the response time, the reputation, etc. •  The application of arithmetical penalties is a consequence of a contract breach and therefore the transition to a different selection using the choices expressed by the customer in the form of preferences Behavioural Penalties •  Related to the behavior of either the customer or the service provider •  The application of behavioral penalties is not always a consequence of a contract breach and so, switching to another choice is not obligatory and even less replacing the service
  • 17. Soft SLA Definition
  • 18. Soft SLA Definition:Preferences & Penalties I prefer to get a payment service and delivery service having response time < 5ms. I also accept services with response time between 5ms and 20ms with preference =0,5 Etc. Response time Preferences If the first Most preferred preference is not <5ms fulfilled during the execution I would apply penalty P7 [5ms,20ms[ >20ms Less preferred
  • 19. Soft SLA Definition Guarantee terms are expressed in terms of preferences and penalties •  Preferences are ranked (most preferred to less preferred) •  Penalties are applied if a preference is not fulfilled The service broker search for service fulfilling the QoS from the most preferred to the less preferred (at design-time) Penalties are applied only at runtime and never at design- time, on the faulty service SSLA document QoS Variable Preference Preferences Penalties Preferences/Penalties variables doamins degree association
  • 20. Extending SCSP Using Penalties SCSP Constraint System Constraints Operations Solution
  • 21. Extending Constraint System SCSP Constraint CS = <S; D{}; V> System S = algebraic structure including preference Constraints values V = QoS variables D{} = Variable domains Operations Penalties into S Solution
  • 22. Extending Constraints Using Penalties SCSP Constraint Def = Definition of the System constraint in terms of preference value Constraints Type = in terms of variable intervening in the constraint Operations Penalties into Def Solution
  • 23. Rewrite operations Logic SCSP Constraint System Combination = combination of the constraints (pref) Constraints Projection = generates the optimal solution Operations Rank generated solutions and keep them all Combination of penalties Solution
  • 24. Extending SCSP Using Penalties SCSP Constraint System Global Preferences Constraints Most preferred + Operations Less preferred - Solution
  • 25. Penalty based SCSPCase Study Penalty based SCSP Constraint System Constraints = Penalty values = Preference values Operations Solutions
  • 26. Penalty based SCSPCase Study Penalty based SCSP Constraint System Constraints Operations Solutions
  • 27. Penalty based SCSPCase Study Penalty based SCSP Constraint System Constraints Operations Solutions
  • 28. Penalty based SCSPCase Study Penalty based SCSP Constraint System Constraints Operations Solutions
  • 29. Proposed Approach LogicInput: Constraints, penalties, table of constraint definitionsOutput: Choices with their possible alternatives orderedBegin For each selection alternative do Combine all the constraints together (apply the min operator); End for; Order the results according to preference values into groups; For each preference value group do Order the elements corresponding to the penalty value; End for;End;
  • 30. Mapping SSLA onto SCSP Solvers
  • 31. Learning Package Overview  Problem Description  Extending SCSP with Penalties & new SLA Model  Conclusions
  • 32. Conclusions1.  Soft constraint-based framework2.  Express QoS properties reflecting both customer preferences and penalties applied to unfitting situations3.  Solution for overconstrained problems –  The application of soft constraints makes it possible to work around overconstrained problems and offer a feasible solution4.  Provide ranked choice to offer more flexibility at design-time to find required services, and at runtime to ensure users’ rights5.  Concept of penalties in SCSP We plan to extend this framework to also deal with behavioral penalties
  • 33. References This presentation is based on [ZBC10]
  • 34. Further S-Cube Reading[ZBC10] Mohamed Anis Zemni, Salima Benbernou, and Manuel Carro A Soft Constraint-Based Approach to QoS-Aware Service Selection In proceeding of the Service-Oriented Computing - 8th International Conference (ICSOC 2010), volume 6470 of Lecture Notes in Computer Science, pages 596-602 San Francisco, CA, USA, December 7-10, 2010
  • 35. Acknowledgements The research leading to these results has received funding from:   The European Community’s Seventh Framework Programme [FP7/2007-2013] under grant agreement 215483 (S-Cube).

×